Abstract
This work aimed at testing the capability of the numerical model SWASH to be implemented in the prototype of the overtopping and flooding forecast system HIDRALERTA for Ericeira harbour. In contrast to the neural network NN_OVERTOPPING2, which is currently implemented in HIDRALERTA, SWASH is able to estimate the flood extension and wave propagation along the domain, which makes it a possible improvement to NN_OVERTOPPING2. The one-dimensional version of the SWASH model was implemented to simulate overtopping at two different profiles (antifer and tetrapods) and calibrated for three storms in 2019 by comparing the simulated overtopping discharge to NN_OVERTOPPING2 results. For the calibration, the Manning coefficient was used to represent the friction of the armour layer. Then, for operational purposes, four expressions to calculate the Manning coefficient were developed based on: the relative crest freeboard, the wave steepness, the incident wave angle and the type of armour layer. The expressions showed small errors between the calculated and calibrated Manning coefficients and highlighted the importance of the incident wave angle to obtain an accurate calibration. Despite an underestimation of the overtopping discharge in some cases, the SWASH model was found to provide overall good results when applied with calculated Manning coefficients and suitable to be implemented in HIDRALERTA.
Funder
Portuguese Foundation of Science and Technology
Subject
Ocean Engineering,Water Science and Technology,Civil and Structural Engineering
Reference31 articles.
1. A Coastal Flooding Database from 1980 to 2018 for the Continental Portuguese Coastal Zone;Tavares;Appl. Geogr.,2021
2. Fortes, C., Reis, M.T., Poseiro, P., Capitão, R., Santos, J., Pinheiro, L., Craveiro, J., Rodrigues, A., Sabino, A., and Ferreira Silva, S. (2014, January 21–26). HIDRALERTA Project—A Flood Forecast and Alert System in Coastal and Port Areas. Proceedings of the IWA – World Water Congress & Exhibition, Lisbon, Portugal.
3. Wave Overtopping at Berm Breakwaters: Review and Sensitivity Analysis of Prediction Models;Pillai;Coast. Eng.,2017
4. Field, C.B., Barros, V., Stocker, T.F., and Dahe, Q. (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, Cambridge University Press.
5. Introduction to RISC-KIT: Resilience-Increasing Strategies for Coasts;Ciavola;Coast. Eng.,2018
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